EnterpriseDB® (EDB™), the database platform company for digital business, announced the general availability of a new version of the EDB Postgres Data Adapter for Hadoop with compatibility for the Apache Spark cluster computing framework. The new version gives organizations the ability to combine analytic workloads based on the Hadoop Distributed File System (HDFS) with operational data in Postgres, using an Apache Spark interface.
The inside Spark channel is a resource for professionals looking to learn about the benefits of Apache Spark
insideBIGDATA was on hand for the recent Spark Summit East 2017 conference in Boston, and one of the more compelling presentations was by Kavitha Mariappan, VP Marketing at Databricks. The talk focused on the premise that despite the tremendous growth and opportunities in big data today, women still play a small role in this arena.
Percipient, a Singapore-based startup, is launching a revolutionary solution to address the memory issues incurred by users of open source platform, Apache Spark. By delivering unified data a priori to the Spark platform, Percipient’s SparkPLUS solution is able to multiply the platform’s computing space, thereby greatly enhancing its utility for real time and analytical applications.
In this talk from Spark Summit East 2016, Prasad Chalasani explores some of the challenges that arise in setting up scalable simulations in a specific application, and share some solutions and lessons learned along the way, in the realms of mathematics and programming.
ODPi Publishes Operations Specification Providing Developers Consistency Across Application Management Tools
ODPi, a nonprofit organization accelerating the open ecosystem of big data solutions, announced the availability of ODPi 2.0, which includes the first release of the ODPi Operations Specification and the Runtime Specification 2.0, to standardize the development model for big data solution and application providers and help enterprises improve installation and management of Hadoop-based applications.
In this special guest feature, Alex Bordei, head of product management at Bigstep, offers 5 examples of how Apache Spark has maximized its user experience – its feel.
In the talk below, Michael Armbrust, gives an overview of some of the exciting new API’s available in Spark 2.0, namely Datasets and Structured Streaming. Together, these APIs are bringing the power of Catalyst, Spark SQL’s query optimizer, to all users of Spark.
IBM (NYSE:IBM) announced IBM Watson Data Platform to help companies gain more valuable insights from data. The platform delivers the world’s fastest data ingestion engine and cognitive-powered decision-making to data professionals, allowing them to collaborate in the IBM Cloud, with the services they prefer. IBM is also making IBM Watson Machine Learning Service available – making machine learning simple with an intuitive, self-service interface.
Databricks®, the company founded by the the team that created the popular Apache® Spark™ project, announced that in collaboration with industry partners, it has broken the world record in the CloudSort Benchmark, a third-party industry benchmarking competition for processing large datasets.
Apache Spark Survey Reveals Increased Growth in Users and New Workloads Including Exploratory Data Science and Machine Learning
In order to better understand Apache Spark’s growing role in big data, Taneja Group conducted a major market research project, surveying approximately 7,000 people. The sample was made up of technical and managerial job roles from around the world directly involved in big data.